Overview

Brought to you by YData

Dataset statistics

Number of variables44
Number of observations8899
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 MiB
Average record size in memory150.0 B

Variable types

Numeric12
Categorical2
Boolean30

Alerts

estado_civil_CASADO is highly overall correlated with estado_civil_SOLTEROHigh correlation
estado_civil_SOLTERO is highly overall correlated with estado_civil_CASADOHigh correlation
estado_cliente_ACTIVO is highly overall correlated with estado_cliente_PASIVO and 2 other fieldsHigh correlation
estado_cliente_PASIVO is highly overall correlated with estado_cliente_ACTIVO and 2 other fieldsHigh correlation
falta_pago_N is highly overall correlated with estado_cliente_ACTIVO and 3 other fieldsHigh correlation
falta_pago_Y is highly overall correlated with estado_cliente_ACTIVO and 3 other fieldsHigh correlation
gastos_ult_12m is highly overall correlated with operaciones_ult_12mHigh correlation
genero_F is highly overall correlated with genero_MHigh correlation
genero_M is highly overall correlated with genero_FHigh correlation
importe_solicitado is highly overall correlated with pct_ingresoHigh correlation
limite_credito_tc is highly overall correlated with nivel_tarjeta_BlueHigh correlation
nivel_tarjeta_Blue is highly overall correlated with limite_credito_tc and 1 other fieldsHigh correlation
nivel_tarjeta_Silver is highly overall correlated with nivel_tarjeta_BlueHigh correlation
operaciones_ult_12m is highly overall correlated with gastos_ult_12mHigh correlation
pct_ingreso is highly overall correlated with importe_solicitadoHigh correlation
situacion_vivienda_ALQUILER is highly overall correlated with situacion_vivienda_HIPOTECAHigh correlation
situacion_vivienda_HIPOTECA is highly overall correlated with situacion_vivienda_ALQUILERHigh correlation
tasa_interes is highly overall correlated with falta_pago_N and 1 other fieldsHigh correlation
situacion_vivienda_OTROS is highly imbalanced (96.3%) Imbalance
situacion_vivienda_PROPIA is highly imbalanced (63.7%) Imbalance
objetivo_credito_MEJORAS_HOGAR is highly imbalanced (57.5%) Imbalance
estado_civil_DESCONOCIDO is highly imbalanced (62.1%) Imbalance
estado_civil_DIVORCIADO is highly imbalanced (61.7%) Imbalance
nivel_educativo_POSGRADO_COMPLETO is highly imbalanced (72.9%) Imbalance
nivel_educativo_POSGRADO_INCOMPLETO is highly imbalanced (70.6%) Imbalance
nivel_tarjeta_Blue is highly imbalanced (64.2%) Imbalance
nivel_tarjeta_Gold is highly imbalanced (90.8%) Imbalance
nivel_tarjeta_Platinum is highly imbalanced (97.8%) Imbalance
nivel_tarjeta_Silver is highly imbalanced (69.6%) Imbalance
id_cliente has unique values Unique
antiguedad_empleado has 1282 (14.4%) zeros Zeros
personas_a_cargo has 787 (8.8%) zeros Zeros

Reproduction

Analysis started2025-05-13 22:34:46.336249
Analysis finished2025-05-13 22:35:01.411072
Duration15.07 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

id_cliente
Real number (ℝ)

Unique 

Distinct8899
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3913216 × 108
Minimum7.0808208 × 108
Maximum8.2834308 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size139.0 KiB
2025-05-14T00:35:01.612239image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum7.0808208 × 108
5-th percentile7.0909773 × 108
Q17.1299492 × 108
median7.1794751 × 108
Q37.7289596 × 108
95-th percentile8.1446105 × 108
Maximum8.2834308 × 108
Range1.20261 × 108
Interquartile range (IQR)59901038

Descriptive statistics

Standard deviation36874783
Coefficient of variation (CV)0.049889296
Kurtosis-0.60717097
Mean7.3913216 × 108
Median Absolute Deviation (MAD)6414450
Skewness0.99743918
Sum6.5775371 × 1012
Variance1.3597496 × 1015
MonotonicityNot monotonic
2025-05-14T00:35:01.695364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
716893683 1
 
< 0.1%
713061558 1
 
< 0.1%
768805383 1
 
< 0.1%
713924283 1
 
< 0.1%
710734308 1
 
< 0.1%
718225683 1
 
< 0.1%
780613758 1
 
< 0.1%
709646433 1
 
< 0.1%
715474083 1
 
< 0.1%
720608658 1
 
< 0.1%
Other values (8889) 8889
99.9%
ValueCountFrequency (%)
708082083 1
< 0.1%
708083283 1
< 0.1%
708084558 1
< 0.1%
708085458 1
< 0.1%
708086958 1
< 0.1%
708095133 1
< 0.1%
708098133 1
< 0.1%
708099183 1
< 0.1%
708100533 1
< 0.1%
708103608 1
< 0.1%
ValueCountFrequency (%)
828343083 1
< 0.1%
828298908 1
< 0.1%
828294933 1
< 0.1%
828291858 1
< 0.1%
828288333 1
< 0.1%
828281733 1
< 0.1%
828236133 1
< 0.1%
828227433 1
< 0.1%
828215508 1
< 0.1%
827968383 1
< 0.1%

edad
Real number (ℝ)

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.538712
Minimum20
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size139.0 KiB
2025-05-14T00:35:01.753866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile21
Q122
median23
Q325
95-th percentile26
Maximum26
Range6
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.5119741
Coefficient of variation (CV)0.064233512
Kurtosis-1.0417363
Mean23.538712
Median Absolute Deviation (MAD)1
Skewness0.10791405
Sum209471
Variance2.2860658
MonotonicityNot monotonic
2025-05-14T00:35:01.804096image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
22 1941
21.8%
23 1926
21.6%
24 1700
19.1%
25 1445
16.2%
26 1185
13.3%
21 696
 
7.8%
20 6
 
0.1%
ValueCountFrequency (%)
20 6
 
0.1%
21 696
 
7.8%
22 1941
21.8%
23 1926
21.6%
24 1700
19.1%
25 1445
16.2%
26 1185
13.3%
ValueCountFrequency (%)
26 1185
13.3%
25 1445
16.2%
24 1700
19.1%
23 1926
21.6%
22 1941
21.8%
21 696
 
7.8%
20 6
 
0.1%

importe_solicitado
Real number (ℝ)

High correlation 

Distinct487
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8179.8264
Minimum500
Maximum35000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size139.0 KiB
2025-05-14T00:35:01.869206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile2000
Q14500
median6500
Q310000
95-th percentile20000
Maximum35000
Range34500
Interquartile range (IQR)5500

Descriptive statistics

Standard deviation5763.5566
Coefficient of variation (CV)0.70460623
Kurtosis2.3548226
Mean8179.8264
Median Absolute Deviation (MAD)2500
Skewness1.52743
Sum72792275
Variance33218585
MonotonicityNot monotonic
2025-05-14T00:35:01.949953image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5000 693
 
7.8%
6000 641
 
7.2%
8000 501
 
5.6%
7000 391
 
4.4%
4000 386
 
4.3%
10000 334
 
3.8%
3000 325
 
3.7%
20000 253
 
2.8%
12000 228
 
2.6%
9000 221
 
2.5%
Other values (477) 4926
55.4%
ValueCountFrequency (%)
500 3
 
< 0.1%
700 1
 
< 0.1%
750 1
 
< 0.1%
800 1
 
< 0.1%
900 1
 
< 0.1%
1000 122
1.4%
1050 1
 
< 0.1%
1100 1
 
< 0.1%
1150 1
 
< 0.1%
1200 60
0.7%
ValueCountFrequency (%)
35000 20
0.2%
34800 1
 
< 0.1%
34000 1
 
< 0.1%
33950 1
 
< 0.1%
33000 1
 
< 0.1%
32500 1
 
< 0.1%
32000 1
 
< 0.1%
31300 1
 
< 0.1%
31050 1
 
< 0.1%
30000 19
0.2%

duracion_credito
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size139.0 KiB
2
3000 
3
2950 
4
2949 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters8899
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row2
3rd row3
4th row2
5th row4

Common Values

ValueCountFrequency (%)
2 3000
33.7%
3 2950
33.1%
4 2949
33.1%

Length

2025-05-14T00:35:02.021483image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T00:35:02.066382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
2 3000
33.7%
3 2950
33.1%
4 2949
33.1%

Most occurring characters

ValueCountFrequency (%)
2 3000
33.7%
3 2950
33.1%
4 2949
33.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8899
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2 3000
33.7%
3 2950
33.1%
4 2949
33.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8899
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2 3000
33.7%
3 2950
33.1%
4 2949
33.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8899
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2 3000
33.7%
3 2950
33.1%
4 2949
33.1%

antiguedad_empleado
Real number (ℝ)

Zeros 

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.9279694
Minimum0
Maximum123
Zeros1282
Zeros (%)14.4%
Negative0
Negative (%)0.0%
Memory size139.0 KiB
2025-05-14T00:35:02.113757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q36
95-th percentile9
Maximum123
Range123
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.3577577
Coefficient of variation (CV)0.85483295
Kurtosis353.76304
Mean3.9279694
Median Absolute Deviation (MAD)2
Skewness10.206277
Sum34955
Variance11.274537
MonotonicityNot monotonic
2025-05-14T00:35:02.170382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0 1282
14.4%
2 1160
13.0%
3 1040
11.7%
5 967
10.9%
6 922
10.4%
1 913
10.3%
4 771
8.7%
7 706
7.9%
8 526
5.9%
9 368
 
4.1%
Other values (3) 244
 
2.7%
ValueCountFrequency (%)
0 1282
14.4%
1 913
10.3%
2 1160
13.0%
3 1040
11.7%
4 771
8.7%
5 967
10.9%
6 922
10.4%
7 706
7.9%
8 526
5.9%
9 368
 
4.1%
ValueCountFrequency (%)
123 2
 
< 0.1%
11 23
 
0.3%
10 219
 
2.5%
9 368
 
4.1%
8 526
5.9%
7 706
7.9%
6 922
10.4%
5 967
10.9%
4 771
8.7%
3 1040
11.7%

ingresos
Real number (ℝ)

Distinct1624
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50870.628
Minimum9600
Maximum500000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size139.0 KiB
2025-05-14T00:35:02.245319image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum9600
5-th percentile20400
Q134000
median47000
Q360000
95-th percentile97000
Maximum500000
Range490400
Interquartile range (IQR)26000

Descriptive statistics

Standard deviation28858.574
Coefficient of variation (CV)0.56729345
Kurtosis20.989299
Mean50870.628
Median Absolute Deviation (MAD)13000
Skewness3.3396389
Sum4.5269772 × 108
Variance8.3281729 × 108
MonotonicityNot monotonic
2025-05-14T00:35:02.324315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60000 386
 
4.3%
30000 313
 
3.5%
50000 304
 
3.4%
40000 242
 
2.7%
45000 217
 
2.4%
55000 201
 
2.3%
65000 197
 
2.2%
48000 194
 
2.2%
36000 185
 
2.1%
42000 176
 
2.0%
Other values (1614) 6484
72.9%
ValueCountFrequency (%)
9600 4
 
< 0.1%
9840 1
 
< 0.1%
9900 1
 
< 0.1%
9960 1
 
< 0.1%
10000 10
0.1%
10560 1
 
< 0.1%
10668 1
 
< 0.1%
10800 3
 
< 0.1%
10980 1
 
< 0.1%
11000 3
 
< 0.1%
ValueCountFrequency (%)
500000 1
 
< 0.1%
306000 1
 
< 0.1%
300000 6
0.1%
287000 1
 
< 0.1%
280000 1
 
< 0.1%
277104 1
 
< 0.1%
275000 1
 
< 0.1%
260000 1
 
< 0.1%
259000 1
 
< 0.1%
255000 1
 
< 0.1%

pct_ingreso
Real number (ℝ)

High correlation 

Distinct72
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.17605012
Minimum0.01
Maximum0.83
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size139.0 KiB
2025-05-14T00:35:02.402764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.04
Q10.09
median0.15
Q30.23
95-th percentile0.39
Maximum0.83
Range0.82
Interquartile range (IQR)0.14

Descriptive statistics

Standard deviation0.10953541
Coefficient of variation (CV)0.62218312
Kurtosis1.4725476
Mean0.17605012
Median Absolute Deviation (MAD)0.07
Skewness1.1242688
Sum1566.67
Variance0.011998006
MonotonicityNot monotonic
2025-05-14T00:35:02.478935image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.1 464
 
5.2%
0.13 406
 
4.6%
0.09 391
 
4.4%
0.11 387
 
4.3%
0.08 386
 
4.3%
0.15 380
 
4.3%
0.12 352
 
4.0%
0.14 348
 
3.9%
0.07 346
 
3.9%
0.17 335
 
3.8%
Other values (62) 5104
57.4%
ValueCountFrequency (%)
0.01 17
 
0.2%
0.02 81
 
0.9%
0.03 198
2.2%
0.04 249
2.8%
0.05 262
2.9%
0.06 304
3.4%
0.07 346
3.9%
0.08 386
4.3%
0.09 391
4.4%
0.1 464
5.2%
ValueCountFrequency (%)
0.83 1
 
< 0.1%
0.77 2
< 0.1%
0.72 1
 
< 0.1%
0.71 2
< 0.1%
0.7 1
 
< 0.1%
0.69 2
< 0.1%
0.68 1
 
< 0.1%
0.67 1
 
< 0.1%
0.65 2
< 0.1%
0.64 3
< 0.1%

tasa_interes
Real number (ℝ)

High correlation 

Distinct306
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.017559
Minimum5.42
Maximum22.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size139.0 KiB
2025-05-14T00:35:02.552095image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum5.42
5-th percentile6.03
Q17.9
median10.99
Q313.47
95-th percentile16.29
Maximum22.11
Range16.69
Interquartile range (IQR)5.57

Descriptive statistics

Standard deviation3.1948187
Coefficient of variation (CV)0.28997518
Kurtosis-0.70367237
Mean11.017559
Median Absolute Deviation (MAD)2.5
Skewness0.18583708
Sum98045.26
Variance10.206867
MonotonicityNot monotonic
2025-05-14T00:35:02.633563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.99 252
 
2.8%
7.51 229
 
2.6%
7.9 189
 
2.1%
7.49 187
 
2.1%
7.88 174
 
2.0%
5.42 171
 
1.9%
9.99 149
 
1.7%
11.49 143
 
1.6%
13.49 132
 
1.5%
11.71 132
 
1.5%
Other values (296) 7141
80.2%
ValueCountFrequency (%)
5.42 171
1.9%
5.79 106
1.2%
5.99 112
1.3%
6 6
 
0.1%
6.03 121
1.4%
6.17 59
 
0.7%
6.39 14
 
0.2%
6.54 72
0.8%
6.62 116
1.3%
6.76 61
 
0.7%
ValueCountFrequency (%)
22.11 1
< 0.1%
21.74 2
< 0.1%
21.36 1
< 0.1%
21.27 1
< 0.1%
21.21 1
< 0.1%
20.89 2
< 0.1%
20.62 1
< 0.1%
20.3 2
< 0.1%
20.25 1
< 0.1%
20.2 1
< 0.1%

estado_credito
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size139.0 KiB
0
6716 
1
2183 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters8899
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
0 6716
75.5%
1 2183
 
24.5%

Length

2025-05-14T00:35:02.705992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-05-14T00:35:02.744392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0 6716
75.5%
1 2183
 
24.5%

Most occurring characters

ValueCountFrequency (%)
0 6716
75.5%
1 2183
 
24.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8899
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 6716
75.5%
1 2183
 
24.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8899
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 6716
75.5%
1 2183
 
24.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8899
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 6716
75.5%
1 2183
 
24.5%

antiguedad_cliente
Real number (ℝ)

Distinct44
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.892347
Minimum13
Maximum56
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size139.0 KiB
2025-05-14T00:35:02.796715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile22
Q131
median36
Q340
95-th percentile50
Maximum56
Range43
Interquartile range (IQR)9

Descriptive statistics

Standard deviation7.99139
Coefficient of variation (CV)0.22264885
Kurtosis0.41415362
Mean35.892347
Median Absolute Deviation (MAD)4
Skewness-0.10311164
Sum319406
Variance63.862314
MonotonicityNot monotonic
2025-05-14T00:35:02.866447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
36 2131
23.9%
37 316
 
3.6%
34 313
 
3.5%
38 306
 
3.4%
40 304
 
3.4%
39 303
 
3.4%
31 296
 
3.3%
33 278
 
3.1%
35 275
 
3.1%
30 262
 
2.9%
Other values (34) 4115
46.2%
ValueCountFrequency (%)
13 63
0.7%
14 15
 
0.2%
15 29
 
0.3%
16 28
 
0.3%
17 35
 
0.4%
18 49
0.6%
19 55
0.6%
20 68
0.8%
21 75
0.8%
22 93
1.0%
ValueCountFrequency (%)
56 94
1.1%
55 36
 
0.4%
54 47
 
0.5%
53 65
0.7%
52 56
 
0.6%
51 70
0.8%
50 84
0.9%
49 127
1.4%
48 136
1.5%
47 145
1.6%

gastos_ult_12m
Real number (ℝ)

High correlation 

Distinct4725
Distinct (%)53.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4426.347
Minimum510
Maximum18484
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size139.0 KiB
2025-05-14T00:35:02.937832image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum510
5-th percentile1289
Q12163.5
median3912
Q34747
95-th percentile14230
Maximum18484
Range17974
Interquartile range (IQR)2583.5

Descriptive statistics

Standard deviation3425.23
Coefficient of variation (CV)0.77382773
Kurtosis3.8141479
Mean4426.347
Median Absolute Deviation (MAD)1314
Skewness2.0311225
Sum39390062
Variance11732201
MonotonicityNot monotonic
2025-05-14T00:35:03.016279image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4253 10
 
0.1%
4509 10
 
0.1%
4518 9
 
0.1%
2229 9
 
0.1%
4077 8
 
0.1%
4042 8
 
0.1%
4037 8
 
0.1%
4313 8
 
0.1%
4275 8
 
0.1%
4220 8
 
0.1%
Other values (4715) 8813
99.0%
ValueCountFrequency (%)
510 1
< 0.1%
530 1
< 0.1%
563 1
< 0.1%
569 1
< 0.1%
594 1
< 0.1%
596 1
< 0.1%
597 1
< 0.1%
615 1
< 0.1%
643 1
< 0.1%
644 1
< 0.1%
ValueCountFrequency (%)
18484 1
< 0.1%
17995 1
< 0.1%
17744 1
< 0.1%
17634 1
< 0.1%
17628 1
< 0.1%
17498 1
< 0.1%
17437 1
< 0.1%
17390 1
< 0.1%
17350 1
< 0.1%
17258 1
< 0.1%

limite_credito_tc
Real number (ℝ)

High correlation 

Distinct5677
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8609.6616
Minimum1438.3
Maximum34516
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size139.0 KiB
2025-05-14T00:35:03.102870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1438.3
5-th percentile1438.3
Q12545.5
median4542
Q311059.5
95-th percentile34516
Maximum34516
Range33077.7
Interquartile range (IQR)8514

Descriptive statistics

Standard deviation9067.7437
Coefficient of variation (CV)1.0532056
Kurtosis1.8372681
Mean8609.6616
Median Absolute Deviation (MAD)2598
Skewness1.6714343
Sum76617379
Variance82223976
MonotonicityNot monotonic
2025-05-14T00:35:03.184402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1438.3 453
 
5.1%
34516 449
 
5.0%
15987 18
 
0.2%
9959 14
 
0.2%
23981 11
 
0.1%
6224 11
 
0.1%
2490 10
 
0.1%
3735 10
 
0.1%
7469 9
 
0.1%
14938 7
 
0.1%
Other values (5667) 7907
88.9%
ValueCountFrequency (%)
1438.3 453
5.1%
1439 2
 
< 0.1%
1440 1
 
< 0.1%
1441 2
 
< 0.1%
1442 1
 
< 0.1%
1443 3
 
< 0.1%
1446 1
 
< 0.1%
1449 2
 
< 0.1%
1451 2
 
< 0.1%
1452 2
 
< 0.1%
ValueCountFrequency (%)
34516 449
5.0%
34496 1
 
< 0.1%
34458 1
 
< 0.1%
34427 1
 
< 0.1%
34198 1
 
< 0.1%
34173 1
 
< 0.1%
34162 1
 
< 0.1%
34140 1
 
< 0.1%
34058 1
 
< 0.1%
33996 1
 
< 0.1%

operaciones_ult_12m
Real number (ℝ)

High correlation 

Distinct125
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.970334
Minimum10
Maximum139
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size139.0 KiB
2025-05-14T00:35:03.266207image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile28
Q145
median67
Q381
95-th percentile106
Maximum139
Range129
Interquartile range (IQR)36

Descriptive statistics

Standard deviation23.52697
Coefficient of variation (CV)0.36211866
Kurtosis-0.35911075
Mean64.970334
Median Absolute Deviation (MAD)17
Skewness0.15413611
Sum578171
Variance553.51834
MonotonicityNot monotonic
2025-05-14T00:35:03.568516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
69 185
 
2.1%
81 181
 
2.0%
71 180
 
2.0%
75 180
 
2.0%
76 173
 
1.9%
78 173
 
1.9%
82 172
 
1.9%
77 172
 
1.9%
70 166
 
1.9%
67 163
 
1.8%
Other values (115) 7154
80.4%
ValueCountFrequency (%)
10 3
 
< 0.1%
11 2
 
< 0.1%
12 4
 
< 0.1%
13 5
 
0.1%
14 8
 
0.1%
15 12
0.1%
16 12
0.1%
17 12
0.1%
18 21
0.2%
19 10
0.1%
ValueCountFrequency (%)
139 1
 
< 0.1%
138 1
 
< 0.1%
134 1
 
< 0.1%
131 6
0.1%
130 5
0.1%
129 5
0.1%
128 9
0.1%
127 10
0.1%
126 10
0.1%
125 12
0.1%

personas_a_cargo
Real number (ℝ)

Zeros 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3527363
Minimum0
Maximum5
Zeros787
Zeros (%)8.8%
Negative0
Negative (%)0.0%
Memory size139.0 KiB
2025-05-14T00:35:03.629825image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile4
Maximum5
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.3007839
Coefficient of variation (CV)0.55288131
Kurtosis-0.6889067
Mean2.3527363
Median Absolute Deviation (MAD)1
Skewness-0.021843935
Sum20937
Variance1.6920388
MonotonicityNot monotonic
2025-05-14T00:35:03.678787image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 2393
26.9%
2 2324
26.1%
1 1616
18.2%
4 1401
15.7%
0 787
 
8.8%
5 378
 
4.2%
ValueCountFrequency (%)
0 787
 
8.8%
1 1616
18.2%
2 2324
26.1%
3 2393
26.9%
4 1401
15.7%
5 378
 
4.2%
ValueCountFrequency (%)
5 378
 
4.2%
4 1401
15.7%
3 2393
26.9%
2 2324
26.1%
1 1616
18.2%
0 787
 
8.8%

situacion_vivienda_ALQUILER
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
True
5439 
False
3460 
ValueCountFrequency (%)
True 5439
61.1%
False 3460
38.9%
2025-05-14T00:35:03.718611image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_HIPOTECA
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
6090 
True
2809 
ValueCountFrequency (%)
False 6090
68.4%
True 2809
31.6%
2025-05-14T00:35:03.749880image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_OTROS
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
8864 
True
 
35
ValueCountFrequency (%)
False 8864
99.6%
True 35
 
0.4%
2025-05-14T00:35:03.780010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

situacion_vivienda_PROPIA
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
8283 
True
 
616
ValueCountFrequency (%)
False 8283
93.1%
True 616
 
6.9%
2025-05-14T00:35:03.807202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
6830 
True
2069 
ValueCountFrequency (%)
False 6830
76.8%
True 2069
 
23.2%
2025-05-14T00:35:03.836046image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
7379 
True
1520 
ValueCountFrequency (%)
False 7379
82.9%
True 1520
 
17.1%
2025-05-14T00:35:03.866271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
8128 
True
 
771
ValueCountFrequency (%)
False 8128
91.3%
True 771
 
8.7%
2025-05-14T00:35:03.898082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
7435 
True
1464 
ValueCountFrequency (%)
False 7435
83.5%
True 1464
 
16.5%
2025-05-14T00:35:03.929167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
7439 
True
1460 
ValueCountFrequency (%)
False 7439
83.6%
True 1460
 
16.4%
2025-05-14T00:35:03.961540image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
7284 
True
1615 
ValueCountFrequency (%)
False 7284
81.9%
True 1615
 
18.1%
2025-05-14T00:35:03.992306image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

falta_pago_N
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
True
7334 
False
1565 
ValueCountFrequency (%)
True 7334
82.4%
False 1565
 
17.6%
2025-05-14T00:35:04.022006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

falta_pago_Y
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
7334 
True
1565 
ValueCountFrequency (%)
False 7334
82.4%
True 1565
 
17.6%
2025-05-14T00:35:04.053720image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_CASADO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
4793 
True
4106 
ValueCountFrequency (%)
False 4793
53.9%
True 4106
46.1%
2025-05-14T00:35:04.086299image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_DESCONOCIDO
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
8245 
True
 
654
ValueCountFrequency (%)
False 8245
92.7%
True 654
 
7.3%
2025-05-14T00:35:04.116858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_DIVORCIADO
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
8234 
True
 
665
ValueCountFrequency (%)
False 8234
92.5%
True 665
 
7.5%
2025-05-14T00:35:04.143572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_civil_SOLTERO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
5425 
True
3474 
ValueCountFrequency (%)
False 5425
61.0%
True 3474
39.0%
2025-05-14T00:35:04.173358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_cliente_ACTIVO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
True
7449 
False
1450 
ValueCountFrequency (%)
True 7449
83.7%
False 1450
 
16.3%
2025-05-14T00:35:04.206417image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

estado_cliente_PASIVO
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
7449 
True
1450 
ValueCountFrequency (%)
False 7449
83.7%
True 1450
 
16.3%
2025-05-14T00:35:04.236252image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

genero_F
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
True
4729 
False
4170 
ValueCountFrequency (%)
True 4729
53.1%
False 4170
46.9%
2025-05-14T00:35:04.267337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

genero_M
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
4729 
True
4170 
ValueCountFrequency (%)
False 4729
53.1%
True 4170
46.9%
2025-05-14T00:35:04.300076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
7583 
True
1316 
ValueCountFrequency (%)
False 7583
85.2%
True 1316
 
14.8%
2025-05-14T00:35:04.329755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
8486 
True
 
413
ValueCountFrequency (%)
False 8486
95.4%
True 413
 
4.6%
2025-05-14T00:35:04.360164image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
8438 
True
 
461
ValueCountFrequency (%)
False 8438
94.8%
True 461
 
5.2%
2025-05-14T00:35:04.387198image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
7133 
True
1766 
ValueCountFrequency (%)
False 7133
80.2%
True 1766
 
19.8%
2025-05-14T00:35:04.417114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
6154 
True
2745 
ValueCountFrequency (%)
False 6154
69.2%
True 2745
30.8%
2025-05-14T00:35:04.448698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
6701 
True
2198 
ValueCountFrequency (%)
False 6701
75.3%
True 2198
 
24.7%
2025-05-14T00:35:04.479459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

nivel_tarjeta_Blue
Boolean

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
True
8294 
False
 
605
ValueCountFrequency (%)
True 8294
93.2%
False 605
 
6.8%
2025-05-14T00:35:04.509217image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

nivel_tarjeta_Gold
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
8795 
True
 
104
ValueCountFrequency (%)
False 8795
98.8%
True 104
 
1.2%
2025-05-14T00:35:04.538322image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

nivel_tarjeta_Platinum
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
8880 
True
 
19
ValueCountFrequency (%)
False 8880
99.8%
True 19
 
0.2%
2025-05-14T00:35:04.566484image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

nivel_tarjeta_Silver
Boolean

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size78.2 KiB
False
8417 
True
 
482
ValueCountFrequency (%)
False 8417
94.6%
True 482
 
5.4%
2025-05-14T00:35:04.594516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Interactions

2025-05-14T00:35:00.067295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:50.161191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:51.044393image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:51.916057image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:52.886089image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:53.856191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.858706image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.642348image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.496179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:57.239391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.090572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.965970image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:35:00.130069image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:50.271335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:51.108555image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:52.005988image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:52.956171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.096122image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.920388image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.710983image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.554732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:57.314791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.164552image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:59.038979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:35:00.191625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:50.336186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:51.175950image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:52.081897image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:53.017370image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.156619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.981497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.779974image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.614732image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:57.384416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.234221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:59.104764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:35:00.263660image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:50.416541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:51.243681image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:52.156250image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:53.112664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.229830image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.050910image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.849972image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.679991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:57.459266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.304374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:59.176460image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:35:00.326573image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:50.499994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:51.311204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:52.236202image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:53.193290image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.298170image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.115016image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.918860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.740768image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:57.529177image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.374703image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-05-14T00:34:53.265905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.362532image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.179388image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.988845image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.804755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:57.596571image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.444617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:59.541177image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:35:00.454622image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:50.641047image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:51.456429image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:52.416170image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:53.350746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.423002image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.238951image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.055209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.864151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:57.663269image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.521446image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:59.609279image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:35:00.523066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:50.709773image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:51.528150image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:52.486088image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:53.444233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.493955image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.306613image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.124507image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.930552image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:57.733505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.602559image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:59.678717image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:35:00.579718image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:50.766128image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:51.595964image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:52.556243image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:53.536220image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.553012image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.366840image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.201608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.984880image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:57.804209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.674283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:59.741997image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:35:00.649797image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:50.836189image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:51.677697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:52.636323image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:53.617108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.626319image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.432808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-05-14T00:34:57.876656image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.754861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:59.814489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:35:00.717162image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:50.911042image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:51.786123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:52.736187image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:53.706038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.720353image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.498701image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.347219image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:57.114354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:57.950887image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.826259image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2025-05-14T00:34:53.795324image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:54.794455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:55.566262image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:56.427820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:57.175947image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.023163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:58.896016image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-05-14T00:34:59.988886image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-05-14T00:35:04.674405image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
antiguedad_clienteantiguedad_empleadoduracion_creditoedadestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOestado_creditofalta_pago_Nfalta_pago_Ygastos_ult_12mgenero_Fgenero_Mid_clienteimporte_solicitadoingresoslimite_credito_tcnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETOnivel_tarjeta_Bluenivel_tarjeta_Goldnivel_tarjeta_Platinumnivel_tarjeta_Silverobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDoperaciones_ult_12mpct_ingresopersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAtasa_interes
antiguedad_cliente1.000-0.0020.000-0.0010.0480.0350.0410.0510.0320.0320.0260.0500.050-0.0250.0190.0190.1120.0390.0120.0090.0000.0210.0290.0000.0240.0100.0290.0190.0000.0080.0000.0000.0130.0320.0170.000-0.0370.035-0.1150.0300.0340.0000.0000.008
antiguedad_empleado-0.0021.0000.0000.1100.0000.0000.0000.0000.0000.0000.0000.0000.0000.0640.0000.0000.0030.1200.190-0.0040.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.058-0.005-0.0030.0000.0000.0000.000-0.065
duracion_credito0.0000.0001.0000.0060.0000.0000.0140.0000.0030.0030.0000.0000.0000.0000.0000.0000.0220.0000.0030.0070.0080.0160.0000.0000.0330.0240.0200.0000.0000.0210.0000.0040.0100.0120.0230.0220.0000.0000.0160.0060.0120.0000.0000.016
edad-0.0010.1100.0061.0000.0160.0000.0130.0060.0140.0140.0420.0000.0000.0090.0000.000-0.0230.0770.1560.0120.0000.0000.0140.0000.0000.0000.0180.0000.0160.0210.1590.0110.2020.0020.0100.0390.007-0.0380.0000.0000.0230.0230.0240.005
estado_civil_CASADO0.0480.0000.0000.0161.0000.2600.2620.7400.0250.0250.0420.0000.0000.1750.0000.0000.0000.0910.0220.0620.0050.0000.0000.0000.0130.0130.0510.0170.0030.0430.0190.0140.0100.0000.0000.0000.1700.0570.0220.0160.0140.0080.0000.000
estado_civil_DESCONOCIDO0.0350.0000.0000.0000.2601.0000.0790.2250.0000.0000.0190.0000.0000.0550.0110.0110.0140.0420.0330.0150.0000.0000.0070.0000.0000.0000.0180.0110.0000.0080.0050.0000.0000.0000.0000.0000.0290.0030.0390.0130.0030.0000.0000.009
estado_civil_DIVORCIADO0.0410.0000.0140.0130.2620.0791.0000.2270.0000.0000.0000.0000.0000.0390.0000.0000.0000.0000.0000.0200.0160.0000.0000.0100.0000.0340.0000.0080.0000.0000.0000.0190.0000.0000.0000.0000.0390.0000.0300.0000.0000.0000.0000.025
estado_civil_SOLTERO0.0510.0000.0000.0060.7400.2250.2271.0000.0170.0170.0310.0000.0000.1410.0140.0140.0000.0690.0070.0320.0210.0000.0000.0000.0050.0000.0410.0160.0000.0330.0070.0000.0150.0000.0000.0050.1400.0380.0380.0220.0170.0000.0000.000
estado_cliente_ACTIVO0.0320.0000.0030.0140.0250.0000.0000.0171.0001.0000.1180.5490.5490.3290.0320.0320.0480.1070.0180.0360.0060.0300.0000.0050.0000.0000.0000.0000.0000.0000.0160.0000.0240.0000.0000.0000.4580.0390.0200.0530.0540.0000.0000.318
estado_cliente_PASIVO0.0320.0000.0030.0140.0250.0000.0000.0171.0001.0000.1180.5490.5490.3290.0320.0320.0480.1070.0180.0360.0060.0300.0000.0050.0000.0000.0000.0000.0000.0000.0160.0000.0240.0000.0000.0000.4580.0390.0200.0530.0540.0000.0000.318
estado_credito0.0260.0000.0000.0420.0420.0190.0000.0310.1180.1181.0000.1900.1900.2330.0250.0250.0190.2100.1180.0000.0000.0040.0080.0080.0000.0000.0000.0000.0000.0000.0950.0640.1120.0610.0140.0410.2410.4010.0000.2060.1650.0220.0990.382
falta_pago_N0.0500.0000.0000.0000.0000.0000.0000.0000.5490.5490.1901.0001.0000.2600.0000.0000.0290.0560.0000.0300.0000.0000.0000.0070.0030.0000.0000.0000.0000.0000.0140.0170.0480.0030.0000.0000.3230.0390.0160.0720.0740.0120.0000.561
falta_pago_Y0.0500.0000.0000.0000.0000.0000.0000.0000.5490.5490.1901.0001.0000.2600.0000.0000.0290.0560.0000.0300.0000.0000.0000.0070.0030.0000.0000.0000.0000.0000.0140.0170.0480.0030.0000.0000.3230.0390.0160.0720.0740.0120.0000.561
gastos_ult_12m-0.0250.0640.0000.0090.1750.0550.0390.1410.3290.3290.2330.2600.2601.0000.2470.247-0.0000.0330.1580.0270.0210.0120.0000.0430.0000.0000.2430.1550.0750.1950.0120.0110.0000.0000.0000.0000.879-0.0730.0590.1510.1800.0000.038-0.187
genero_F0.0190.0000.0000.0000.0000.0110.0000.0140.0320.0320.0250.0000.0000.2471.0001.0000.0000.1710.1130.4420.0000.0070.0000.0130.0000.0000.0840.0380.0000.0740.0080.0000.0000.0000.0000.0070.1680.0680.0000.0390.0410.0000.0000.005
genero_M0.0190.0000.0000.0000.0000.0110.0000.0140.0320.0320.0250.0000.0000.2471.0001.0000.0000.1710.1130.4420.0000.0070.0000.0130.0000.0000.0840.0380.0000.0740.0080.0000.0000.0000.0000.0070.1680.0680.0000.0390.0410.0000.0000.005
id_cliente0.1120.0030.022-0.0230.0000.0140.0000.0000.0480.0480.0190.0290.029-0.0000.0000.0001.000-0.010-0.0000.0160.0130.0000.0000.0080.0210.0000.0100.0000.0000.0130.0370.0000.0000.0000.0390.0240.006-0.008-0.0080.0300.0270.0000.000-0.026
importe_solicitado0.0390.1200.0000.0770.0910.0420.0000.0690.1070.1070.2100.0560.0560.0330.1710.171-0.0101.0000.3480.0390.0270.0050.0000.0000.0210.0000.0800.0350.0160.0660.0000.0170.0310.0000.0000.045-0.0000.7390.0310.1900.1680.0110.0560.073
ingresos0.0120.1900.0030.1560.0220.0330.0000.0070.0180.0180.1180.0000.0000.1580.1130.113-0.0000.3481.0000.0380.0150.0000.0000.0250.0000.0150.0920.0550.0270.0670.0000.0210.0580.0440.0200.0340.130-0.2960.0190.1560.1200.0000.086-0.026
limite_credito_tc0.009-0.0040.0070.0120.0620.0150.0200.0320.0360.0360.0000.0300.0300.0270.4420.4420.0160.0390.0381.0000.0000.0070.0000.0000.0000.0180.5590.2880.1350.4750.0230.0000.0000.0000.0060.0000.0300.0200.0490.0000.0220.0000.0120.004
nivel_educativo_DESCONOCIDO0.0000.0000.0080.0000.0050.0000.0160.0210.0060.0060.0000.0000.0000.0210.0000.0000.0130.0270.0150.0001.0000.0910.0960.2070.2780.2380.0000.0000.0000.0000.0000.0000.0230.0190.0000.0000.0000.0000.0280.0110.0000.0000.0150.000
nivel_educativo_POSGRADO_COMPLETO0.0210.0000.0160.0000.0000.0000.0000.0000.0300.0300.0040.0000.0000.0120.0070.0070.0000.0050.0000.0070.0911.0000.0490.1090.1460.1250.0000.0000.0000.0000.0000.0000.0170.0000.0000.0000.0350.0180.0000.0000.0000.0000.0000.012
nivel_educativo_POSGRADO_INCOMPLETO0.0290.0000.0000.0140.0000.0070.0000.0000.0000.0000.0080.0000.0000.0000.0000.0000.0000.0000.0000.0000.0960.0491.0000.1150.1550.1330.0000.0000.0130.0000.0000.0170.0050.0000.0070.0000.0000.0190.0120.0000.0000.0000.0040.000
nivel_educativo_SECUNDARIO_COMPLETO0.0000.0000.0000.0000.0000.0000.0100.0000.0050.0050.0080.0070.0070.0430.0130.0130.0080.0000.0250.0000.2070.1090.1151.0000.3320.2840.0070.0000.0090.0000.0000.0000.0000.0000.0000.0170.0000.0000.0100.0060.0000.0000.0000.011
nivel_educativo_UNIVERSITARIO_COMPLETO0.0240.0000.0330.0000.0130.0000.0000.0050.0000.0000.0000.0030.0030.0000.0000.0000.0210.0210.0000.0000.2780.1460.1550.3321.0000.3820.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0000.0050.0000.0000.0120.000
nivel_educativo_UNIVERSITARIO_INCOMPLETO0.0100.0000.0240.0000.0130.0000.0340.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0150.0180.2380.1250.1330.2840.3821.0000.0000.0000.0060.0000.0140.0000.0060.0000.0000.0050.0000.0110.0160.0050.0030.0000.0000.000
nivel_tarjeta_Blue0.0290.0000.0200.0180.0510.0180.0000.0410.0000.0000.0000.0000.0000.2430.0840.0840.0100.0800.0920.5590.0000.0000.0000.0070.0000.0001.0000.4000.1660.8850.0000.0000.0000.0000.0000.0000.1750.0000.0300.0170.0250.0000.0040.000
nivel_tarjeta_Gold0.0190.0000.0000.0000.0170.0110.0080.0160.0000.0000.0000.0000.0000.1550.0380.0380.0000.0350.0550.2880.0000.0000.0000.0000.0000.0000.4001.0000.0000.0210.0000.0000.0000.0000.0000.0000.0910.0000.0290.0000.0070.0000.0030.019
nivel_tarjeta_Platinum0.0000.0000.0000.0160.0030.0000.0000.0000.0000.0000.0000.0000.0000.0750.0000.0000.0000.0160.0270.1350.0000.0000.0130.0090.0000.0060.1660.0001.0000.0000.0000.0000.0000.0000.0000.0070.0600.0000.0000.0000.0000.0000.0000.000
nivel_tarjeta_Silver0.0080.0000.0210.0210.0430.0080.0000.0330.0000.0000.0000.0000.0000.1950.0740.0740.0130.0660.0670.4750.0000.0000.0000.0000.0000.0000.8850.0210.0001.0000.0000.0000.0000.0000.0040.0000.1390.0000.0140.0160.0190.0000.0000.000
objetivo_credito_EDUCACIÓN0.0000.0000.0000.1590.0190.0050.0000.0070.0160.0160.0950.0140.0140.0120.0080.0080.0370.0000.0000.0230.0000.0000.0000.0000.0000.0140.0000.0000.0000.0001.0000.2490.1690.2440.2430.2590.0000.0250.0000.0000.0000.0000.0000.035
objetivo_credito_INVERSIONES0.0000.0000.0040.0110.0140.0000.0190.0000.0000.0000.0640.0170.0170.0110.0000.0000.0000.0170.0210.0000.0000.0000.0170.0000.0000.0000.0000.0000.0000.0000.2491.0000.1390.2010.2000.2130.0000.0050.0000.0450.0000.0000.0910.030
objetivo_credito_MEJORAS_HOGAR0.0130.0000.0100.2020.0100.0000.0000.0150.0240.0240.1120.0480.0480.0000.0000.0000.0000.0310.0580.0000.0230.0170.0050.0000.0000.0060.0000.0000.0000.0000.1690.1391.0000.1360.1350.1440.0190.0370.0240.0330.0260.0000.0070.046
objetivo_credito_PAGO_DEUDAS0.0320.0000.0120.0020.0000.0000.0000.0000.0000.0000.0610.0030.0030.0000.0000.0000.0000.0000.0440.0000.0190.0000.0000.0000.0000.0000.0000.0000.0000.0000.2440.2010.1361.0000.1960.2080.0110.0000.0130.0430.0000.0000.0920.014
objetivo_credito_PERSONAL0.0170.0000.0230.0100.0000.0000.0000.0000.0000.0000.0140.0000.0000.0000.0000.0000.0390.0000.0200.0060.0000.0000.0070.0000.0000.0000.0000.0000.0000.0040.2430.2000.1350.1961.0000.2080.0270.0090.0340.0170.0200.0000.0000.017
objetivo_credito_SALUD0.0000.0000.0220.0390.0000.0000.0000.0050.0000.0000.0410.0000.0000.0000.0070.0070.0240.0450.0340.0000.0000.0000.0000.0170.0000.0050.0000.0000.0070.0000.2590.2130.1440.2080.2081.0000.0000.0130.0000.0400.0380.0000.0000.027
operaciones_ult_12m-0.0370.0580.0000.0070.1700.0290.0390.1400.4580.4580.2410.3230.3230.8790.1680.1680.006-0.0000.1300.0300.0000.0350.0000.0000.0000.0000.1750.0910.0600.1390.0000.0000.0190.0110.0270.0001.000-0.0840.0560.1350.1640.0000.038-0.219
pct_ingreso0.035-0.0050.000-0.0380.0570.0030.0000.0380.0390.0390.4010.0390.039-0.0730.0680.068-0.0080.739-0.2960.0200.0000.0180.0190.0000.0150.0110.0000.0000.0000.0000.0250.0050.0370.0000.0090.013-0.0841.0000.0230.0530.0390.0370.0450.091
personas_a_cargo-0.115-0.0030.0160.0000.0220.0390.0300.0380.0200.0200.0000.0160.0160.0590.0000.000-0.0080.0310.0190.0490.0280.0000.0120.0100.0000.0160.0300.0290.0000.0140.0000.0000.0240.0130.0340.0000.0560.0231.0000.0000.0000.0000.015-0.010
situacion_vivienda_ALQUILER0.0300.0000.0060.0000.0160.0130.0000.0220.0530.0530.2060.0720.0720.1510.0390.0390.0300.1900.1560.0000.0110.0000.0000.0060.0050.0050.0170.0000.0000.0160.0000.0450.0330.0430.0170.0400.1350.0530.0001.0000.8510.0760.3410.143
situacion_vivienda_HIPOTECA0.0340.0000.0120.0230.0140.0030.0000.0170.0540.0540.1650.0740.0740.1800.0410.0410.0270.1680.1200.0220.0000.0000.0000.0000.0000.0030.0250.0070.0000.0190.0000.0000.0260.0000.0200.0380.1640.0390.0000.8511.0000.0390.1840.148
situacion_vivienda_OTROS0.0000.0000.0000.0230.0080.0000.0000.0000.0000.0000.0220.0120.0120.0000.0000.0000.0000.0110.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0370.0000.0760.0391.0000.0090.028
situacion_vivienda_PROPIA0.0000.0000.0000.0240.0000.0000.0000.0000.0000.0000.0990.0000.0000.0380.0000.0000.0000.0560.0860.0120.0150.0000.0040.0000.0120.0000.0040.0030.0000.0000.0000.0910.0070.0920.0000.0000.0380.0450.0150.3410.1840.0091.0000.000
tasa_interes0.008-0.0650.0160.0050.0000.0090.0250.0000.3180.3180.3820.5610.561-0.1870.0050.005-0.0260.073-0.0260.0040.0000.0120.0000.0110.0000.0000.0000.0190.0000.0000.0350.0300.0460.0140.0170.027-0.2190.091-0.0100.1430.1480.0280.0001.000

Missing values

2025-05-14T00:35:00.956427image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-05-14T00:35:01.218632image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

id_clienteedadimporte_solicitadoduracion_creditoantiguedad_empleadoingresospct_ingresotasa_interesestado_creditoantiguedad_clientegastos_ult_12mlimite_credito_tcoperaciones_ult_12mpersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDfalta_pago_Nfalta_pago_Yestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOgenero_Fgenero_Mnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETOnivel_tarjeta_Bluenivel_tarjeta_Goldnivel_tarjeta_Platinumnivel_tarjeta_Silver
0713061558.022350003123.0590000.5916.02136.01088.04010.024.02.0TrueFalseFalseFalseFalseFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseFalse
1768805383.021100025.096000.1011.14039.01144.012691.042.03.0FalseFalseFalseTrueTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalse
2818770008.025550031.096000.5712.87144.01291.08256.033.05.0FalseTrueFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalse
3713982108.0233500024.0655000.5315.23136.01887.03418.020.03.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseFalse
4710821833.0243500048.0544000.5514.27154.01314.09095.026.01.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueTrueFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseFalseFalseTrueFalseFalseFalse
5769911858.021250022.099000.257.14134.01171.03313.020.04.0FalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseFalse
6709106358.0263500038.0771000.4512.42121.0816.04716.028.03.0TrueFalseFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseFalseTrueTrueFalseFalseFalse
7810347208.0243500045.0789560.4411.11146.01330.034516.031.04.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseTrueFalseFalseTrueTrueFalseFalseFalseFalseFalseFalseTrueFalseFalse
8818906208.0243500028.0830000.428.90127.01538.029081.036.00.0TrueFalseFalseFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseTrueFalseFalseTrueFalseFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseFalseTrue
9710930508.021160036.0100000.1614.74136.01350.022352.024.03.0FalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseFalseTrueTrueFalseFalseFalse
id_clienteedadimporte_solicitadoduracion_creditoantiguedad_empleadoingresospct_ingresotasa_interesestado_creditoantiguedad_clientegastos_ult_12mlimite_credito_tcoperaciones_ult_12mpersonas_a_cargosituacion_vivienda_ALQUILERsituacion_vivienda_HIPOTECAsituacion_vivienda_OTROSsituacion_vivienda_PROPIAobjetivo_credito_EDUCACIÓNobjetivo_credito_INVERSIONESobjetivo_credito_MEJORAS_HOGARobjetivo_credito_PAGO_DEUDASobjetivo_credito_PERSONALobjetivo_credito_SALUDfalta_pago_Nfalta_pago_Yestado_civil_CASADOestado_civil_DESCONOCIDOestado_civil_DIVORCIADOestado_civil_SOLTEROestado_cliente_ACTIVOestado_cliente_PASIVOgenero_Fgenero_Mnivel_educativo_DESCONOCIDOnivel_educativo_POSGRADO_COMPLETOnivel_educativo_POSGRADO_INCOMPLETOnivel_educativo_SECUNDARIO_COMPLETOnivel_educativo_UNIVERSITARIO_COMPLETOnivel_educativo_UNIVERSITARIO_INCOMPLETOnivel_tarjeta_Bluenivel_tarjeta_Goldnivel_tarjeta_Platinumnivel_tarjeta_Silver
10113710841183.022900034.0650000.149.63034.015577.013940.0114.01.0FalseTrueFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseTrueFalseFalseTrueFalseFalseFalse
10114713899383.025950024.0610000.167.51050.014596.03688.0120.01.0TrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalse
10115772366833.025950032.0680000.147.14040.015476.04003.0117.02.0TrueFalseFalseFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseFalse
10116710638233.024950034.0586500.1416.49125.08764.04277.069.02.0TrueFalseFalseFalseFalseFalseFalseFalseFalseTrueTrueFalseFalseFalseTrueFalseFalseTrueFalseTrueTrueFalseFalseFalseFalseFalseTrueFalseFalseFalse
10117708564858.022950041.0690000.1415.33120.09338.034516.073.02.0TrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalse
10118713755458.025700049.0650000.1111.66036.010310.09959.063.01.0FalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseTrueFalseTrueFalseFalseFalseTrueFalseTrueTrueFalseFalseFalseFalseFalseTrueFalseFalseFalse
10119717406983.022957531.0430000.226.62036.08395.05281.062.02.0TrueFalseFalseFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseTrueFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueFalseTrueFalseFalseFalse
10120716506083.022960020.0216000.447.49136.010291.05409.060.01.0TrueFalseFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseFalseFalseTrueFalseFalseTrueFalseFalseFalse
10121714337233.023960023.0220000.4413.16125.010294.010388.061.02.0TrueFalseFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseTrueTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseTrue
10122716893683.024360048.0650040.0613.49047.06009.014657.053.03.0FalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseTrueFalseTrueTrueFalseFalseFalseFalseFalseFalseTrueTrueFalseFalseFalse